Porous crystalline materials for memories and neuromorphic computing systems.

Porous crystalline materials usually include metal-organic frameworks (MOFs), covalent organic frameworks (COFs), hydrogen-bonded organic frameworks (HOFs) and zeolites, which exhibit exceptional porosity and structural/composition designability, promoting the increasing attention in memory and neuromorphic computing systems in the last decade. From both the perspective of materials and devices, it is crucial to provide a comprehensive and timely summary of the applications of porous crystalline materials in memory and neuromorphic computing systems to guide future research endeavors. Moreover, the utilization of porous crystalline materials in electronics necessitates a shift from powder synthesis to high-quality film preparation to ensure high device performance. This review highlights the strategies for preparing porous crystalline materials films and discusses their advancements in memory and neuromorphic electronics. It also provides a detailed comparative analysis and presents the existing challenges and future research directions, which can attract the experts from various fields (e.g., materials scientists, chemists, and engineers) with the aim of promoting the applications of porous crystalline materials in memory and neuromorphic computing systems.

A van der Waals Integrated Damage-Free Memristor Based on Layered 2D Hexagonal Boron Nitride.

2D materials with intriguing properties have been widely used in optoelectronics. However, electronic devices suffered from structural damage due to the ultrathin materials and uncontrolled defects at interfaces upon metallization, which hindered the development of reliable devices. Here, a damage-free Au/h-BN/Au memristor is reported using a clean, water-assisted metal transfer approach by physically assembling Au electrodes onto the layered h-BN which minimized the structural damage and undesired interfacial defects. The memristors demonstrate significantly improved performance with the coexistence of nonpolar and threshold switching as well as tunable current levels by controlling the compliance current, compared with devices with evaporated contacts. The devices integrated into an array show suppressed sneak path current and can work as both logic gates and latches to implement logic operations allowing in-memory computing. Cross-sectional scanning transmission electron microscopy analysis validates the feasibility of this nondestructive metal integration approach, the crucial role of high-quality atomically sharp interface in resistive switching, and a direct observation of percolation path. The underlying mechanism of boron vacancies-assisted transport is further supported experimentally by conductive atomic force microscopy free from process-induced damage, and theoretically by ab initio simulations.

Filament Engineering of Two-Dimensional h-BN for a Self-Power Mechano-Nociceptor System.

The switching variability caused by intrinsic stochasticity of the ionic/atomic motions during the conductive filaments (CFs) formation process largely limits the applications of diffusive memristors (DMs), including artificial neurons, neuromorphic computing and artificial sensory systems. In this study, a DM device with improved device uniformity based on well-crystallized two-dimensional (2D) h-BN, which can restrict the CFs formation from three to two dimensions due to the high migration barrier of Ag+ between h-BN interlayer, is developed. The BN-DM has potential arrayable feature with high device yield of 88%, which can be applied for building a reservoir computing system for digital pattern recognition with high accuracy rate of 96%, and used as an artificial nociceptor to sense the external noxious stimuli and mimic the important biological nociceptor properties. By connecting the BN-DM to a self-made triboelectric nanogenerator (TENG), a self-power mechano-nociceptor system, which can successfully mimic the important nociceptor features of "threshold", "relaxation" and "allodynia" is designed.

Reconfigurable 2D WSe2 -Based Memtransistor for Mimicking Homosynaptic and Heterosynaptic Plasticity.

The mimicking of both homosynaptic and heterosynaptic plasticity using a high-performance synaptic device is important for developing human-brain-like neuromorphic computing systems to overcome the ever-increasing challenges caused by the conventional von Neumann architecture. However, the commonly used synaptic devices (e.g., memristors and transistors) require an extra modulate terminal to mimic heterosynaptic plasticity, and their capability of synaptic plasticity simulation is limited by the low weight adjustability. In this study, a WSe2 -based memtransistor for mimicking both homosynaptic and heterosynaptic plasticity is fabricated. By applying spikes on either the drain or gate terminal, the memtransistor can mimic common homosynaptic plasticity, including spiking rate dependent plasticity, paired pulse facilitation/depression, synaptic potentiation/depression, and filtering. Benefitting from the multi-terminal input and high adjustability, the resistance state number and linearity of the memtransistor can be improved by optimizing the conditions of the two inputs. Moreover, the device can successfully mimic heterosynaptic plasticity without introducing an extra terminal and can simultaneously offer versatile reconfigurability of excitatory and inhibitory plasticity. These highly adjustable and reconfigurable characteristics offer memtransistors more freedom of choice for tuning synaptic weight, optimizing circuit design, and building artificial neuromorphic computing systems.

Near-Infrared Artificial Synapses for Artificial Sensory Neuron System.

The computing based on artificial neuron network is expected to break through the von Neumann bottleneck of traditional computer, and to greatly improve the computing efficiency, displaying a broad prospect in the application of artificial visual system. In the specific structural layout, it is a common method to connect the discrete photodetector with the artificial neuron in series, which enhances the complexity of signal recognition, conversion and storage. In this work, organic small molecule IR-780 iodide is inserted into the memory device as both the charge trapping layer and near-infrared (NIR) photoresponsive film. Through electrical and optical regulation, artificial synaptic functions including short-term plasticity, long-term plasticity, and spike rate dependence are realized. In the established artificial sensory neuron system, NIR optical pulses can significantly improve the spiking rate. Moreover, the spiking neural networks are further constructed by simulation for handwritten digit classification. This research may contribute to the development of light driven neural robots, optical signal encryption, and neural computing.

Recent advances in synthesis and application of perovskite quantum dot based composites for photonics, electronics and sensors.

In recent years, halide perovskite quantum dots (HP-QDs) based composites have been widely developed and used in various applications owing to their unique photonic, electronic and mechanical properties, as well as high stability to water, oxygen, heat and illumination. Remarkable efforts have been made in the synthesis and applications of these materials in photonics, electronics, sensors and other fields. Besides these topics, we also cover enhancement of optoelectronic properties as well as chemical, thermal and photostability of HP-QDs-based composites. We hope this review will promote both the development and applications of perovskite-based materials.

A mechanistic study of geminal dicationic ionic liquids as mobile phase additives for improving the separation performance of high-performance liquid chromatography.

Due to the acidity and strong polarity of auxinic herbicides, separation of these compounds in food and environmental samples is a great challenge. In this study, 12 geminal dicationic ionic liquids (GDILs) were synthesized and used as mobile phase additives to separate six auxinic herbicides. The effects of the kind of dication, the length of linkage chain, the kind of anion, the concentration of GDILs, and the pH of mobile phase for the separation were investigated in detail. Compared with [C4MIm][BF4], GDILs ([C8(MIm)2][BF4]2) showed higher resolution, better peak shape, and lower retention factor. The separation performance of additives was in the order of [C8(MIm)2][BF4]2 > [C8(MPy)2][BF4]2, [(C4)2MPiz][BF4]2, [C8(MMo)2][BF4]2, [C4MIm][BF4], [C8(MPid)2][BF4]2 > [C8(HBOc)2][BF4]2 > TBAB. GDILs showed the best separation under the following conditions: cation: imidazolium; length of linkage chain: 8; anion: BF4-; mobile phase pH: 3; concentration: 5 mmol L-1. The separation mechanism of GDILs may mainly be due to their symmetric structure and the abundance of positive charge sites which could help GDILs shield the residual silanol and interact with analytes more efficiently to improve the peak shapes, resolution, and retention. In addition, the GDILs in the mobile phase and anions adsorbed on the stationary phase also greatly affected the separation. GDILs used as mobile phase additives to separate auxinic herbicides showed high efficiency separation and low damage to HPLC columns, and the developed chromatographic method had excellent linearity, accuracy, precision, and repeatability. The application and mechanism study of GDILs in HPLC would be instructive to determine and separate acid herbicides in food and environmental samples. Graphical abstract As HPLC mobile phase additives, GDILs show high separation performance due to their unique symmetric structures.

Development and validation of an HPLC method for determination of Amikacin in water samples by solid phase extraction and pre-column derivatization.

This work presents a rapid and sensitive high performance liquid chromatography method for the determination of amikacin in water samples with solid phase extraction and pre-column derivatization. Amikacin residue was extracted from water samples with solid phase extraction cartridge. Then the extraction solution was derivatized with 4-chloro-3,5-dinitrobenzotrifluoride in the presence of triethylamine at 70°C in 20 min. The amikacin derivative was separated on a C18 column and detected by application of UV detection at 238 nm. The limit of detection is 0.2 µg/L with a signal-to-noise ratio of 3 and linearity is established over the concentration range from 0 to 500.0 µg/L. Recoveries of the amikacin in three types of water samples are from 87.5 % to 99.6 % and RSDs are 2.1 %-4.5 %. This method can be used for the quantification of amikacin residues in water samples.

An in-sensor humidity computing system for contactless human-computer interaction.

Being capable of processing large amounts of redundant data and decreasing power consumption, in-sensor computing approaches play significant roles in neuromorphic computing and are attracting increasing interest in perceptual information processing. Herein, we proposed a high performance humidity-sensitive memristor based on a Ti/graphene oxide (GO)/HfOx/Pt structure and verified its potential for application in remote health management and contactless human-machine interfaces. Since GO possesses abundant hydrophilic groups (carbonyl, epoxide, and hydroxyl), the memristor shows a high humidity sensitivity, fast response, and wide response range. By utilizing the proton-modulated redox reaction, humidity exposure to the memristor induces a dynamic change in the switching between high and low resistance states, ensuring essential synaptic learning functions, such as paired-pulse facilitation, spike number-dependent plasticity, and spike amplitude-dependent plasticity. More importantly, based on the humidity-induced salient features originating from the abundant hydrophilic functional groups in GO, we have implemented a noncontact human-machine interface utilizing the respiratory mode in humans, demonstrating the potential of promoting health monitoring applications and effectively blocking virus transmission. In addition, the high recognition accuracy of contactless handwriting in a 5 × 5 array artificial neural network was successfully achieved, which is attributed to the excellent emulated synaptic behaviors. This study provides a feasible method to develop an excellent humidity-sensitive memristor for constructing efficient in-sensor computing for application in health management and contactless human-computer interaction.

Covalent Organic Frameworks for Neuromorphic Devices.

Neuromorphic computing could enable the potential to break the inherent limitations of conventional von Neumann architectures, which has led to widespread research interest in developing novel neuromorphic memory devices, such as memristors and bioinspired artificial synaptic devices. Covalent organic frameworks (COFs), as crystalline porous polymers, have tailorable skeletons and pores, providing unique platforms for the interplay with photons, excitons, electrons, holes, ions, spins, and molecules. Such features encourage the rising research interest in COF materials in neuromorphic electronics. To develop high-performance COF-based neuromorphic memory devices, it is necessary to comprehensively understand materials, devices, and applications. Therefore, this Perspective focuses on discussing the use of COF materials for neuromorphic memory devices in terms of molecular design, thin-film processing, and neuromorphic applications. Finally, we provide an outlook for future directions and potential applications of COF-based neuromorphic electronics.

Inorganic Perovskite Quantum Dot-Based Strain Sensors for Data Storage and In-Sensor Computing.

Although remarkable improvement has been achieved in stretchable strain sensors, challenges still exist in aspects including intelligent sensing, simultaneous data processing, and scalable fabrication techniques. In this work, a strain-sensitive device is presented by fabricating a CsPbBr3 quantum dots (QDs) floating-gate field-effect transistor (FET) sensing array on thin polyimide (PI) films. The FET exhibits an excellent on/off ratio (>103) and a large memory window (>2 V). With the introduction of CsPbBr3 QDs as the trapping layer, an additional UV response is obtained because of the photogenerated charge carriers that significantly enhance the source-drain current (IDS) of the device. At each electrical state, the IDS varies with the strains and the sensing range is from compressive +12.5% to tensile -10.8%. Excellent data retainability and mechanical durability demonstrate the high quality and reliability of the fabricated sensors. Furthermore, synapse functions including long-term potentiation (LTP), long-term depression (LTD), etc., are emulated at the device level. Linearity factor changes of LTP/LTD in different sensing scenarios demonstrate the reliability of the device and further confirm the different sensing mechanisms with/without UV illumination. Our results exhibit the potential of transistor-based devices for multifunctional intelligent sensing.

Stacked Two-Dimensional MXene Composites for an Energy-Efficient Memory and Digital Comparator.

Two-dimensional MXene has enormous potential for application in industry and academia owing to its surface hydrophilicity and excellent electrochemical properties. However, the application of MXene in optoelectronic memory and logical computing is still facing challenges. In this study, an optoelectronic resistive random access memory (RRAM) based on silver nanoparticles (Ag NPs)@MXene-TiO2 nanosheets (AMT) was prepared through a low-cost and facile hydrothermal oxidation process. The fabricated device exhibited a typical bipolar switching behavior and controllable SET voltage. Furthermore, we successfully demonstrated a 4-bit in-memory digital comparator with AMT RRAMs, which can replace five logic gates in a traditional approach. The AMT-based digital comparator may open the door for future integrated functions and applications in optoelectronic data storage and simplify the complex logic operations.

Modulation of Binary Neuroplasticity in a Heterojunction-Based Ambipolar Transistor.

To keep pace with the upcoming big-data era, the development of a device-level neuromorphic system with highly efficient computing paradigms is underway with numerous attempts. Synaptic transistors based on an all-solution processing method have received growing interest as building blocks for neuromorphic computing based on spikes. Here, we propose and experimentally demonstrated the dual operation mode in poly{2,2-(2,5-bis(2-octyldodecyl)-3,6-dioxo-2,3,5,6-tetrahydropyrrolo[3,4-c]pyrrole-1,4-diyl)dithieno[3,2-b]thiophene-5,5-diyl-alt-thiophen-2,5-diyl}(PDPPBTT)/ZnO junction-based synaptic transistor from ambipolar charge-trapping mechanism to analog the spiking interfere with synaptic plasticity. The heterojunction formed by PDPPBTT and ZnO layers serves as the basis for hole-enhancement and electron-enhancement modes of the synaptic transistor. Distinctive synaptic responses of paired-pulse facilitation (PPF) and paired-pulse depression (PPD) were configured to achieve the training/recognition function for digit image patterns at the device-to-system level. The experimental results indicate the potential application of the ambipolar transistor in future neuromorphic intelligent systems.

Configurable multi-state non-volatile memory behaviors in Ti3C2 nanosheets.

MXenes have drawn considerable attention in both academia and industry due to their attractive properties, such as a combination of metallic conductivity and surface hydrophilicity. However, to the best of our knowledge, the potential use of MXenes in non-volatile resistive random access memories (RRAMs) has rarely been reported. In this paper, we first demonstrated a RRAM device with MXene (Ti3C2) as the active component. The Ti3C2-based RRAM exhibited typical bipolar switching behavior, long retention characteristics, low SET voltage, good mechanical stability and excellent reliability. By adjusting different compliance currents in the SET process, multi-state information storage was achieved. The charge trapping assisting hopping process is considered to be the main mechanism of resistive switching for this fabricated Ti3C2-based RRAM, which was verified by conductive atomic force microscopy (C-AFM) and Kelvin probe force microscopy (KPFM). Moreover, this flexible Ti3C2-based RRAM, with good mechanical stability and long retention properties, was successfully fabricated on a plastic substrate. Ti3C2-based RRAMs may open the door to additional applications and functionalities, with high potential for application in flexible electronics.

Light Driven Active Transition of Switching Modes in Homogeneous Oxides/Graphene Heterostructure.

Depending on the mobile species involved in the resistive switching process, redox random access memories and conductive bridge random access memories are widely studied with distinct switching mechanisms. Although the two resistance switching types have faithfully proved to be electrochemically linked in metal oxide-based memristive devices, the corresponding photo-induced transition has not yet been realized. Here, a photo-induced transition through the integration of a graphene layer into a titanium oxide-based memory device is demonstrated. Coupled with Raman mapping and an electron energy loss spectroscopy technique, the photo-induced interaction at the heterostructure of graphene/titanium oxide are considered to dominate the transition process. Moreover, a negative differential resistance effect is observed by controlling the applied voltage, which can be credited to the saturation of trap centers (oxygen vacancies) and the increase of interfacial barrier at the graphene/titanium oxide heterojunction.

Infrared-Sensitive Memory Based on Direct-Grown MoS2 -Upconversion-Nanoparticle Heterostructure.

Photonic memories as an emerging optoelectronic technology have attracted tremendous attention in the past few years due to their great potential to overcome the von Neumann bottleneck and to improve the performance of serial computers. Nowadays, the decryption technology for visible light is mature in photonic memories. Nevertheless, near-infrared (NIR) photonic memristors are less progressed. Herein, an NIR photonic memristor based on MoS2 -NaYF4 :Yb3+ , Er3+ upconversion nanoparticles (UCNPs) nanocomposites is designed. Under excitation by 980 nm NIR light, the UCNPs show emissions well overlapping with the absorption band of the MoS2 nanosheets. The heterostructure between the MoS2 and the UCNPs acting as excitons generation/separation centers remarkably improves the NIR-light-controlled memristor performance. Furthermore, in situ conductive atomic force microscopy is employed to elucidate the photo-modulated memristor mechanism. This work provides novel opportunities for NIR photonic memory that holds promise in future multifunctional robotics and electronic eyes.

Developing ionic liquid forms of picloram with reduced negative effects on the aquatic environment.

As a widely used herbicide, picloram has been frequently detected in the aquatic environment due to its high leaching potential and low adsorption by soil. To reduce aquatic environmental risk of this herbicide caused by leaching and runoff, five herbicidal ionic liquids (HILs) based on picloram were prepared by pairing isopropylamine, octylamine, octadecylamine, 1-methylimidazole, 4-methylmorpholine respectively. Their physicochemical properties including water solubility, octanol-water partition coefficient, surface activity, leaching, as well as soil adsorption were compared. The results showed that these properties could be adjusted by appropriate selection of counter cations. The HILs with long alkyl chains in cations had low water solubility and leaching characteristics, good surface tension and lipophilicity, as well as high soil adsorption. Compared with currently used picloram in the forms of potassium salts, HIL3 had more excellent herbicidal activity against broadleaf weeds and may offer a lower use dosage. The HILs based on picloram can reduce its negative effects on the aquatic environment and can be used as a desirable alternative to commercial herbicidal formulations of picloram in future.

Preparation and characterization of indole-3-butyric acid nanospheres for improving its stability and utilization.

Indole-3-butyric acid (IBA) is an efficient plant growth regulator for promoting germination and the formation of rooting of various plants. Since it is unstable and presents the low utilization ratio, there is a compelling need to design an environmentally friendly formulation for IBA, which can reduce the loss of degradation and improve its utilization. Nano-sized controlled-release formulations can provide better durability and penetrate through the plant epidermis to efficiently deliver the agrochemicals to the target tissues. In this work, a kind of novel nano controlled-release formulation was prepared by conjugating the IBA and 3-glycidoxypropyltrimethoxysilane (GPTMS) through a covalent cross-linking reaction, and subsequently hydrolyzation and polycondensation with tetraethoxysilane. The resulting nanospheres were characterized by Fourier transform infrared spectroscopy, ultraviolet spectrophotometry, scanning electron microscope, and thermal gravity analysis. The results showed that the obtained nanospheres had a remarkable loading efficiency of IBA (about 43% w/w). The formation of covalent between IBA and GPTMS enabled the nanospheres with a good chemical stability that could protect against photo-degradation effectively. The released rate of the IBA from nanospheres was related to the temperature, pH value. With increased temperature as well as acidity and alkality, the release of the IBA was sped up. The IBA could also be released effectively from IBA-silica nanospheres by esterase, and the sustainable release characteristics of IBA-silica nanospheres were in conformity with the Ritger and Peppas equation. The IBA-silica nanospheres displayed excellent dual stimuli-responsive properties under esterase and weak acid conditions, and could obviously promote the growth of root and bud of pea. Thus, the IBA silica nanospheres prepared by covalent cross-linking reaction have a good potential application as a controlled-release formulation and environmentally-friendly plant growth regulator.

In-situ ionic liquid dispersive liquid-liquid microextraction using a new anion-exchange reagent combined Fe3O4 magnetic nanoparticles for determination of pyrethroid pesticides in water samples.

In this work, in-situ ionic liquid dispersive liquid-liquid microextraction combined ultrasmall Fe3O4 magnetic nanoparticles was developed as a kind of pretreatment method to detect pyrethroid pesticides in water samples. New anion-exchange reagents including Na[DDTC] and Na[N(CN)2] were optimized for in-situ extraction pyrethroids, which showed enhanced microextraction performance. Pyrethroids were enriched by hydrophilic ionic liquid [P4448][Br] (aqueous solution, 200 µL, 0.2 mmol mL-1) reaction in-situ with anion-exchange reagent Na[N(CN)2] (aqueous solution, 300 µL, 0.2 mmol mL-1) forming hydrophobic ionic liquid as extraction agent in water sample (10 mL). Ultrasmall superparamagnetic iron oxide nanoparticles (30 mg) were used to collect the mixture of ionic liquid and pyrethroids followed by elution with acetonitrile. The extraction of ionic liquid strategies was unique and efficiently fulfilled with high enrichment factors (176-213) and good recoveries (80.20-117.31%). The method was successively applied to the determination of pyrethroid pesticides in different kinds of water samples with the limits of detection ranged from 0.16 to 0.21 µg L-1. The proposed method is actually nanometer-level microextraction (average size 80 nm) with the advantages of simplicity, rapidity, and sensitivity.

Pectin-conjugated silica microcapsules as dual-responsive carriers for increasing the stability and antimicrobial efficacy of kasugamycin.

Kasugamycin is an aminoglycoside antibiotic originally isolated from Streptomyces kasugaensis, which has been widely used for the management of plant diseases. However, photo-thermal instability and low efficiency limit its application. Therefore, it is an urgent task to prevent unwanted loss of kasugamycin and ensure maximum bioactivity at target site. In this work, a novel formulation of kasugamycin that responds to different biological stimuli produced by pests was prepared using silica microcapsules crosslinked with pectin via special disulfide bonds. The results demonstrated that the silica-SS-pectin microcapsules had a high loading efficiency (20% w/w) and could effectively enhance the thermal and light stability of kasugamycin. The microcapsules displayed excellent pectinase and glutathione dual-responsive properties and the release kinetics investigated by Riger-Peppas model suggested combination of various release mechanisms. Compared with kasugamycin wettable powder, the microcapsules possessed sustained and improved antimicrobial efficacy against Erwinia carotovora. Thus, the dual-responsive microcapsules potentially have agricultural application as a controlled release system.